The International Association for Automation and Robotics in Construction
Publications / CCC 2025 - Zadar, Croatia
BIM-BASED ASSESSMENT OF ECOLOGICAL, ECONOMIC AND SOCIAL SUSTAINABILITY FOR PLANNING WITHOUT SUSTAINABILITY EXPERTISE
The challenges of climate change and resource scarcity are significant for the construction sector. In particular, materials such as concrete and masonry produce high CO? emissions and require large amounts of limited raw materials. There are currently no practical tools for assessing building materials against a wide range of sustainability criteria in accordance with the client's requirements in the early stages of planning. Furthermore, it is difficult to check whether the requirements of the criteria have been satisfied during this process without specialist knowledge. This study develops a prototype using the graphical programming interface Dynamo to create an automated system for assessing the sustainability of building materials. Ecological, economic and social data from existing databases are linked with quantities from digital building models in the authoring software Revit. The system scores materials based on defined criteria and weights. It then provides an automated result to quantify the sustainability of the building, without requiring the expertise of the designer. The results of the sustainability assessment are ultimately added to and stored within the project's building information. The prototype was validated using the masonry walls in the building model. The results show that the prototype enables a standardized and simple sustainability assessment of building materials. For example, it can evaluate not only the amount of CO? equivalents, but also the associated life cycle costs, and the material-related transmission factor can be automatically determined and evaluated. A limitation of the paper is that energy efficiency is only considered for building materials, while other construction systems such as installations are not included. Therefore, the overall assessment is limited to the materials without considering the interactions with other systems. Furthermore, the connection to external data sources is static, so automatic data updates are not possible. A dynamic integration of new data would improve the adaptability and timeliness of the approach.